# VDF AI VDF AI is an enterprise AI agent orchestration platform for coordinating agents, models, tools, retrieval, and workflows under centralized governance. Run it as a managed cloud service or deploy it in a private cloud, data centre, sovereign environment, AWS account, or air-gapped infrastructure. - Findings24: - Website: - Pricing: Freemium - Categories: Developer Tools ## What is VDF AI? VDF AI is an enterprise AI orchestration platform for turning AI agents and models into governed workflows. It coordinates multi-agent execution, retrieval from enterprise knowledge sources, model selection, tool calls, approvals, and result validation while recording the execution path for review. The platform is available as a managed cloud service or as a self-deployed installation in a data centre, private cloud, sovereign environment, AWS account, or air-gapped setting. Its product suite includes VDF AI Networks for multi-agent orchestration, VDF AI Agents for deployable agent workflows, VDF AI Chat for private-RAG conversations, and VDF AI Data for data preparation and model validation. ## What can VDF AI do? ### Governed multi-agent Networks Decompose a request into typed sub-tasks, map dependencies, select agents, tools, and models at runtime, and validate the result before returning it. Execution paths are recorded. ### Enterprise retrieval and knowledge grounding Use private RAG and knowledge-graph capabilities to ground responses in connected enterprise information rather than relying only on pasted context. ### Runtime model routing Select models against task complexity, cost, latency, and capability. Routing decisions are logged for operational review. ### Workflow governance and audit trails Apply centralized controls for access, permissions, policies, retrieval, tool calls, and execution logging so decisions can be reconstructed later. ### Private deployment options Run the platform in VDF AI’s managed cloud or deploy it on private infrastructure, including on-premises, private-cloud, sovereign, and air-gapped environments. ### Usage and operational reporting Monitor cost and energy metrics, usage, execution activity, and governance data. Capacity licensing includes dashboards, monthly consumption statements, and usage alerts. ## Use Cases ### Private knowledge assistants Build chat or agent experiences that retrieve information from private enterprise sources while keeping the data and deployment under the organization’s control. ### Complex cross-system workflows Coordinate multiple agents, models, tools, APIs, databases, business systems, decisions, and approval steps as one repeatable workflow. ### Model-cost optimization Route different tasks to suitable models based on complexity, latency, capability, and cost, then review the routing and usage records. ### Regulated or sovereign AI operations Operate agents and retrieval inside a company data centre, private or sovereign environment, or disconnected infrastructure where external API dependencies are not acceptable. ### Production AI operations Move a validated use case from a pilot into a controlled production workflow with defined inputs, owners, access controls, monitoring, and auditable execution records. ## Frequently Asked Questions ### Where can VDF AI run? VDF AI can run as a managed cloud service or be deployed on an organization’s infrastructure, including a data centre, private cloud, sovereign environment, AWS account, or air-gapped environment. The on-premises platform uses container deployment. ### How does a request move through the platform? VDF AI parses intent, breaks the request into typed sub-tasks, maps dependencies, selects agents, tools, and models, coordinates work that may run in parallel, validates the result, and records the execution path and outcome. ### Does VDF AI support private enterprise data? Yes. The platform provides enterprise RAG and knowledge-graph grounding, and its deployment options are intended for organizations that need to keep data, models, agents, and infrastructure within their own perimeter. ### How is on-premises usage licensed? On-premises capacity licensing uses an annual organization-wide pool with separate token and platform-transaction meters. Capacity is shared across included environments, while human users are unlimited. VDF AI provides a usage dashboard, monthly consumption statements, and alerts. ### Can teams start without buying an on-premises capacity bundle? The managed cloud version has a free Starter plan with no credit card required. VDF AI also describes a controlled 90-day pilot for on-premises evaluation, with a defined allowance, throughput ceiling, and one non-production environment; the pilot fee is credited toward an annual Capacity Bundle ordered shortly afterward. ## Quick Facts - **Category**: Enterprise AI platform - **Primary functions**: AI agent orchestration, private RAG, model routing, workflow governance - **Deployment**: Managed cloud, private cloud, on-premises, sovereign, or air-gapped - **Products**: VDF AI Networks, VDF AI Agents, VDF AI Chat, and VDF AI Data - **Cloud entry point**: Free Starter plan; no credit card required - **Pricing model**: Cloud plans and annual on-premises capacity licensing